When thinking about a large language model (LLM) input and output, a text Gen AI prompt (sometimes accompanied by other modalities such as image prompts) is the input the model uses to predict a specific output.
You don’t need to be a data scientist or a machine learning engineer – everyone can write an effective gen AI prompt.
However, crafting the most effective prompt can be complicated. Many aspects of your prompt affect its efficacy: the model you use, the model’s training data, the model configurations, your word-choice, style and tone, structure, and context all matter. Therefore, prompt engineering is an iterative process. Inadequate prompts can lead to ambiguous, inaccurate responses, and can hinder the model’s ability to provide meaningful output.
Released in April 2025, this 60+ whitepaper goes beyond “prompting 101” and dives deep into advanced prompt engineering with Gemini AI and for large language models (LMMs) in general. This whitepaper discusses various prompting techniques:
- Zero prompting
- Few shot prompting
- System prompting
- Role prompting
- Contextual prompting
- Step-back prompting
- Chain of thought
- Self consistency
- Tree of thoughts
- ReAct
The whitepaper also explores:
- Ways you can automate your prompts
- The challenges of gen AI like, including problems that can happen when your prompts are insufficient
- Best practices on how to become better at prompts
Dive Deep into Gen AI Prompts
